# coding: utf-8

"""
    Vayu Events Api

    The Vayu Event Ingestion API is a RESTful API that allows you to submit events for processing and storage. The API is secured using the Bearer Authentication scheme with JWT tokens. To obtain a JWT token, please contact Vayu at team@withvayu.com 

    The version of the OpenAPI document: 2.3.1
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from datetime import datetime
from typing import Any, ClassVar, Dict, List, Optional

from pydantic import BaseModel, Field, StrictStr

try:
    from typing import Self
except ImportError:
    from typing_extensions import Self

class EventInput(BaseModel):
    """
    EventInput
    """ # noqa: E501
    name: StrictStr = Field(description="The distinctive label assigned to an event, serving as a critical identifier for categorizing and pricing events within the system's backend infrastructure.")
    timestamp: datetime = Field(description="The temporal marker denoting the exact moment of event occurrence.")
    customer_alias: StrictStr = Field(description="A pseudonymous or otherwise obfuscated identifier uniquely assigned to each customer.", alias="customerAlias")
    data: Optional[Dict[str, Any]] = Field(default=None, description="A schema-less JSON object encapsulating miscellaneous attributes and metrics associated with the event.")
    ref: Optional[StrictStr] = Field(default=None, description="A universally unique identifier (UUID) or other form of high-entropy string serving as an immutable reference for each event entry.")
    __properties: ClassVar[List[str]] = ["name", "timestamp", "customerAlias", "data", "ref"]

    model_config = {
        "populate_by_name": True,
        "validate_assignment": True,
        "protected_namespaces": (),
    }


    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Self:
        """Create an instance of EventInput from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> Dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        _dict = self.model_dump(
            by_alias=True,
            exclude={
            },
            exclude_none=True,
        )
        return _dict

    @classmethod
    def from_dict(cls, obj: Dict) -> Self:
        """Create an instance of EventInput from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "name": obj.get("name"),
            "timestamp": obj.get("timestamp"),
            "customerAlias": obj.get("customerAlias"),
            "data": obj.get("data"),
            "ref": obj.get("ref")
        })
        return _obj


